In the last fifty years, purely digital Von Neumannian computing has progressed considerably. Nonetheless, even the most powerful computers using the most advanced algorithms are unable to quickly perform apparently simple processes, such as image interpretation, that are however performed in a fraction of a second by the human brain. The human brain indeed operates massively parallelly and analogically, unlike current computers. Chip-based analog neuromimetic circuits, which are intended to reproduce the operation of the human brain, make it possible to go beyond conventional architectures. Neural-network architectures work on the basis of learning methods: a circuit is caused to react in the desired manner to a given input. This is achieved by adjusting the values of the components of the circuit such as to converge on the desired output for a given input. Chip-based implementation therefore requires the use of nanometric, analog, reconfigurable and rapid components.
Until 2008, chip-based neuromimetic circuits were entirely built using transistors. Notably, several transistors were used to reproduce the plasticity of a single synapse connecting two neurons.
In 2008 however, the Hewlett-Packard team headed by Stanley Williams published several patents and articles proposing neural circuits built using one transistor per neuron and a “memristor” per synapse connecting two neurons (D. B. Strukov et al., Nature 453, 80 (2008) and J. J. Yang et al., Nature Nano. 3, 429 (2008)). A memristor is a nanometric resistor having a value configurable within a continuous range by the electric charge that previously crossed it. In the case of neural circuits, the main application thereof is to simulate the plasticity of synapses on a chip. A Hewlett-Packard memristor forms a structure comprising an insulating layer inserted between ordinary metal layers. By applying a current to the structure, oxygen vacancies are created, which migrate under the effect of the voltage and induce a resistance change. These memristors work on the basis of the effect of ion electromigration. Unfortunately, this ion electromigration effect involves high operating temperatures and therefore a potential fragility of the device. Above all, however, this ion electromigration effect results in low operating speeds, since it is related to the mobility of the ions: the resistance of Hewlett-Packard memristors changes very slowly.
This is why the applicant has turned to a technology radically different to the technologies used in known memristors, i.e. magnetoresistance. Indeed, the applicant has demonstrated in experiments that it is possible to move a magnetic wall in a magnetic element by spin transfer, in one direction or the other according to the sign of the current applied to the magnetic element. The applicant has notably measured this effect in spin valves, which are devices in which two magnetic layers are separated by a metal layer (J. Grollier et al., Appl. Phys. Lett. 83, 509 (2003)). Furthermore, it has recently been suggested (X. Wang et al., IEEE Electron Device Letters 30, 741 (2009)) that these spin valves could be used to make memristors. Surprisingly, this last publication gives no implementation details, since the realization of a memristor using a spin valve is difficult to imagine. This is because the memristive effect of the spin valves is negligible, because they provide limited magnetoresistance, about 10%. Consequently, a spin valve can only provide low-value resistance. This is why the realization of a memristor using a spin valve is difficult to envisage.
In 2005, the applicant filed international patent application WO 2006/064022 A1, which discloses a device having two magnetic elements separated by an insulating element. The device makes it possible to switch reproducibly between two stable magnetization states identifiable with logic states “0” or “1”, thereby enabling the storage of information. Switching between two magnetization states is effected by moving a magnetic wall in one of the magnetic elements between two stable positions. Unfortunately, this device does not make it possible to continuously vary the resistance within a range, since the magnetic wall only has two stable positions to which they gravitate irremediably. It therefore only provides two resistance values, each corresponding to one of the two magnetization states. Consequently, it is not a memristor.